A Review on Breast Cancer Detection for Histopathology Images Using Deep Learning

A prevalent and deadly kind of cancer in women is breast cancer. The likelihood of surviving breast cancer may rise if it is detected early. Breast cancer diagnosis and treatment are greatly aided by breast histopathology image analysis. This results to the development of efficient Deep Learning algorithms in this field, which helps histopathologists achieve successful analytical results. This research presents an overview of methodologies for deep learning-based image analysis of breast histopathology. Histopathology image datasets that are frequently utilized like BreaKHis, MITOS dataset, Camelyon etc. are analysed. Finally, various performance metrics for assessing the effectiveness of breast cancer prediction algorithms are presented. The purpose is to review current deep learning models for detection and classification of breast cancer using histopathological images.